1. Field of the Invention
The present invention relates to data transform methods and apparatuses, data processing methods and apparatuses, and programs. More particularly, the invention relates to a data transform method and apparatus, a data processing method and apparatus, and a program therefor, which are suitable for distributing sample data (trial data) of content to users.
2. Description of the Related Art
Due to widespread use of communication network technologies including the Internet, improvements in information compression techniques, and enhanced integration or density of information recording media, pay distribution of digital content including various multimedia data, such as audio, still images, moving pictures, and a combination of audio and moving pictures, for example, movies, to users are conducted via communication networks.
A store that sells package media, such as compact disks (CDs) or mini-disks (MDs) (trademark), that is, recording media in which digital content is recorded, is installed with an information terminal, a so-called multimedia kiosk (MMK), in which many pieces of digital content including music data are stored. This enables the store not only to sell package media, but also to sell digital content.
A user brings a recording medium, such as an MD, and inserts it into the MMK. The user then selects the title of digital content to be purchased by referring to a menu screen, and pays for the content. Payment may be made by cash, electronic money, or electronic settlement by a credit card or a prepaid card. The MMK records the selected digital content data on the recording medium inserted by the user by performing predetermined processing.
As described above, digital content sellers can sell digital content by using the MMK, and can also distribute digital content to users via, for example, the Internet.
Content can be distributed more effectively not only by selling package media having content recorded thereon, but also by selling digital content itself.
In order to distribute digital content while protecting the copyright, techniques, for example, those disclosed in Japanese Unexamined Patent Application Publication Nos. 2001-103047 and 2001-325460 can be used. Portions of digital content other than portions that are permitted to preview or listen to on a trial basis are encrypted, and the digital content is distributed. Then, only users who have purchased a decryption key for the corresponding encryption are permitted to preview or listen to the entire content. As a known encryption method, the initial value of a random number sequence is given to a bit string of a pulse code modulation (PCM) digital audio signal as a key signal, and a bit string obtained by performing an exclusive-OR of the generated 0/1 random number sequence and the above-described PCM bit string is used as an encrypted bit stream. The digital content encrypted as described above is recorded on a recording medium by using, for example, the above-described MMK, or is transmitted via a network to be distributed to a user. Unless the user who has obtained the digital content data has a key, the user is only permitted to preview or listen to an unencrypted portion. If the encrypted portion is played back without being decrypted, only noise is heard.
There have been improvements in techniques for compressing audio data and broadcasting it, distributing audio data via a network, and recording compressed data on various recording media, such as magneto-optical disks.
There are various techniques for coding audio signals with high efficiency. For example, in a block-less frequency-band division technique, i.e., a so-called “sub-band coding (SBC)”, an audio signal in the time domain is divided into a plurality of frequency bands and coded without dividing them into blocks. In a block frequency-band division technique, i.e., a so-called “transform coding”, a signal in the time domain is transformed (spectrum transform) into a signal in the frequency domain so as to be divided into a plurality of frequency bands. The signal components are then coded in each band. Another high-efficiency coding technique, which is a combination of the above-described sub-band coding and transform coding, has also been considered. In this case, for example, after sub-band division is performed in the above-described SBC, signal components in each sub band are transformed into signal components in the frequency domain, and are then coded in each band.
Filters used in the above-described high-efficiency coding methods include quadrature mirror filters (QMF), details of which are described in R. E. Crochiere, “Digital Coding of Speech in Subbands” (Bell Syst. Tech. J., vol. 55, No. 8, 1974). An equal-bandwidth filtering technique is described in Joseph H. Rothweiler, “Polyphase Quadrature Filters—a New Subband Coding Technique” (ICASSP 83, BOSTON).
As the above-described spectrum transform, for example, an input audio signal is formed into blocks in predetermined time units (frames), and discrete Fourier transform (DFT), discrete cosine transform (DCT), or modified DCT (MDCT) is performed on the signal components in each block, thereby transforming a time-domain signal into a frequency-domain signal. Details of MDCT are described in J. P. Princen and A. B. Bradley, (Univ. of Surrey, Royal Melbourne Inst. of Tech.), “Subband/Transform Coding Using Filter Bank Designs Based on Time Domain Aliasing Cancellation” (ICASSP 1987).
In the spectrum transform using the above-described DFT or DCT, when the spectrum transform is performed in a time block consisting of M samples, M items of independent real-number data are obtained. Generally, in order to reduce distortion at the connections between time blocks, one block overlaps with each of the adjacent blocks by N/2 samples, and thus, a total of N samples are overlapped with the two adjacent blocks. On average, in DFT or DCT, M items of real-number data are quantized and coded for (M+N) samples.
In contrast, in the spectrum transform using the above-described MDCT, when the spectrum transform is performed in a time block consisting of M samples, M items of real-number data is obtained. One block overlaps with each of the adjacent blocks by M/2 samples, and thus, a total of M samples are overlapped with the two adjacent blocks. Accordingly, in MDCT, M items of real-number data are obtained from 2M samples. On average, in MDCT, M items of real-number data are quantized and coded for M samples.
In a decoding apparatus, coded data obtained by performing MDCT is inverse-transformed in each block, and the resulting waveform components are added together while interfering with each other so as to reconstruct a waveform signal.
Generally, the spectrum frequency resolution is enhanced as the time block for spectrum transform becomes longer, thereby allowing energy to be concentrated in specific spectral components. As described above, in MDCT, the spectrum transform is performed with an increased block length by overlapping samples between adjacent blocks, and the number of spectral signal components remains the same as the original number of samples. By using such MDCT, coding can be performed with higher efficiency than by using DFT or DCT. Also, by allowing a sufficiently long overlapping portion between adjacent blocks, inter-block distortion of the waveform signal can be reduced.
By quantizing signal components divided into sub bands by using a filter or spectrum transform, bands in which quantizing noise is generated can be controlled, and high-efficiency coding can be performed by utilizing the masking effect. Before performing quantizing, if signal components in each band are normalized by the maximum of the absolute values of the signal components in the corresponding band, higher efficiency coding can be performed.
When quantizing signal components divided into frequency bands, the bandwidths may be determined by considering, for example, human acoustic characteristics. That is, generally, an audio signal may be divided into a plurality of bands (for example, 25 bands) so that the bandwidth of the higher bands, which are referred to as the “critical bands”, becomes greater.
When the bandwidths are determined so that the bandwidth of critical bands becomes greater, data in each band is coded according to a predetermined bit distribution or an adaptive bit allocation.
It is now assumed, for example, that coefficient data obtained by the above-described MDCT processing is coded by an adaptive bit allocation. In this case, the number of bits are adaptively allocated to MDCT coefficient data in each band, and the MDCT coefficient data is then coded. The following two bit allocation techniques are known.
One technique is disclosed in R. Zelinski and P. Noll, “Adaptive Transform Coding of Speech Signals” (IEEE Transactions of Acoustics, Speech, and Signal Processing, Vol. ASSP-25, No. 4, August 1977). In this technique, bit allocation is performed according to the magnitude of the signal in each band, and thus, the quantizing noise spectrum becomes flat to minimize the noise energy. However, since the masking effect is not employed, the actual sound is not acoustically optimal for reducing noise.
The other technique is disclosed in M. A. Kransner (Massachusetts Institute of Technology), “The Critical Band Coder—Digital Encoding of the Perceptual Requirements of the Auditory System” (ICASSP 1980). In this method, by utilizing the masking effect, fixed bit allocation is performed for determining a signal-to-noise (S/N) ratio required for each band. However, due to the fixed bit allocation, even when the characteristic of a sinusoidal wave input is measured, a precise value cannot be obtained.
In order to overcome the above drawbacks, the following high-efficiency coding apparatus has been proposed. All the bits available to bit allocation are divided into bits for fixed bit allocation and bits for adaptive bit allocation. The division ratio of the two types of bit allocations is determined by an input signal, and the division ratio of the fixed bit allocation becomes higher as the signal spectrum becomes smoother.
According to the above-described coding apparatus, many bits can be allocated to blocks containing specific spectral components, such as sinusoidal waves, in which energy is concentrated, thereby making it possible to considerably improve the overall S/N ratio characteristics. Generally, the human acoustic characteristics are extremely sensitive to signals having sharp spectral components. Accordingly, an improved S/N ratio by using this method is effective not only in enhancing precise measurements, but also in improving the sound quality.
Many other bit allocation techniques have been proposed. Because of increasingly precise acoustic models and higher performance of coding apparatuses, even higher efficiency coding is possible not only in terms of measured values, but also for human acoustic characteristics. In these methods, the bit-allocation real-number reference value is determined so that the calculated S/N ratio can be achieved as faithfully as possible, and the integer approximating the reference value is used as the number of allocation bits.
In Japanese Patent Application No. 5-152865 or WO94/28633 filed by the present inventors, another coding method has been proposed in which tone components that are particularly important in an acoustic sense, i.e., signal components in which energy is concentrated, are extracted from a spectrum signal, and are separately coded from the other spectral components. According to this coding method, audio signals can be efficiently coded with a high compression ratio with very little degradation.
In forming code strings, quantizing-precision information and normalizing-coefficient information are first coded with a predetermined number of bits in each band, and the resulting normalized and quantized spectrum signal is coded. A high-efficiency coding method in which the number of bits representing the quantizing precision differs according to the band is described in ISO/IEC 11172-3: 1993(E), 1933. In this standard, the number of bits indicating the quantizing-precision information becomes smaller as the band becomes higher.
Instead of directly coding quantizing precision information, the quantizing-precision information may be determined from the normalizing-coefficient information in a decoding apparatus. According to this method, however, the relationship between the normalizing-coefficient information and the quantizing-precision information is determined when the standard is set, which makes it impossible to introduce the quantizing precision based on more precise acoustic models in the future. Additionally, if the compression ratio has a range, the relationship between the normalizing-coefficient information and the quantizing-precision information has to be determined according to each range.
Another known coding method is disclosed in D. A. Huffman, “A Method for Construction of Minimum Redundancy Codes” (Proc. I.R.E., 40, p. 1098, 1952). In this method, a quantized spectrum signal is coded more efficiently by using variable codes.
The signal coded as described above can be encrypted and distributed, as in PCM signals, in which case, those who have not obtained the corresponding key are unable to play back the original signal. Alternatively, instead of encrypting a coded bit string, a PCM signal may be transformed into a random signal, which is then coded for compression. It is also impossible for users who have not obtained the corresponding key to play back the original signal, and only noise is heard.
Distribution of sample data (trial data) of content data promotes sales of the content data. The sample data includes data to be played back with lower quality than the original data and data for playing back part of the original data (for example, only refrains of an original piece of music). A user plays back the sample data, and if the user likes it, the user purchases a key for decrypting the encrypted data to play back the original content data. Alternatively, the user purchases original content data or a recording medium in which the original content data is recorded.
In the above-described content protection methods, however, the entire data cannot be played back, or only noise is heard. Accordingly, these methods cannot be used for, for example, distributing recording media storing audio data recorded with a relatively low audio quality as sample data. Even if data scrambled by one of the above-described methods is distributed to a user, the user is unable to understand the content of the data.
When encrypting signals subjected to high-efficiency coding, it is very difficult to maintain the compression efficiency while providing code strings that are meaningful for regular playback means. That is, when a code string generated by performing high-efficiency coding is scrambled and is then played back, as described above, only noise is heard, and also, playback means may not operate at all if the scrambled code string is not compatible with the original high-efficiency code standard.
Also, when a scrambled PCM signal is coded with high efficiency and the amount of information is reduced by utilizing the acoustic characteristics, coding becomes irreversible. Accordingly, the scrambled PCM signal cannot be correctly reconstructed when the coded signal is decoded. Thus, it is very difficult to descramble the signal.
Therefore, a method for precisely descrambling the signal must be employed by sacrificing the compression efficiency.
Japanese Unexamined Patent Application Publication No. 10-135944 (corresponding to U.S. Pat. No. 6,081,784) filed by the present inventors discloses the following audio coding method. In this method, among spectral signal components coded from a music signal, signal components only in higher bands are encrypted and are distributed as sample data, thereby enabling users to play back unencrypted signal components in a narrow band without a corresponding key. In this method, signal components only in higher bands are encrypted, and also, high-band bit allocation information is replaced by dummy data, true bit allocation information being recorded at a position ignored by playback decoders.
According to this method, a user receives the distributed sample data, plays it back, and then purchases a key for decrypting the sample data that the user likes into the original data. The user is then able to play back a desired piece of music correctly in all the bands and enjoy the music with high sound quality.
Some content providers desire to restrict the use of sample data obtained by one of the above-described known methods for the purpose of undertaking temporary sales promotion before starting to sell the content. The users who have obtained the sample data based on the above-described known methods are, however, disadvantageously able to utilize the sample data without limitations.
In order to overcome this drawback, a method for controlling a playback operation of sample data disclosed in Japanese Unexamined Patent Application Publication No. 2001-282258 has been proposed. This method enables copyright holders to restrict the use of sample data based on conditions, such as the date, period, the number of uses, and the time for the user is allowed to preview or listen to the sample data.
If the playback operation of sample data is restricted by various conditions as described above, a user must know the status of the sample data, for example, whether the sample data can be played back or until when the sample data can be played back. For example, if content is music data and the use of such data is restricted by the period, sample data that has expired the period cannot be played back. In this case, the user must find the reason why the music data cannot be played back through a display device provided for a playback apparatus.
However, the user is not able to recognize that the sample data has expired unless the user checks with the display device, or the user may consider that the playback device has broken down.